Transfer Function of Assembly Process with Compliant Non-ideal Parts

Das, Abhishek; Franciosa, Pasquale; Prakash, P.K.S.; Ceglarek, Darek

doi:10.1016/j.procir.2014.03.195

Cited by 20 publications

(8 citation statements)

References 22 publications

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“…[1] (P2) automation level of boiling point (Automation percentage of welding in related station). [2] (P3) dimensional and geometrical quality importance of assemblage (IQG index). [3] (P4) the percentage of backbone and stability of mechanisms (from the viewpoint of CMM maintenance).…”

Section: -Describing the Methodsmentioning

confidence: 99%

Dimensional calibration (CMM) scheduling of manufactured fixture’s locators, using the M-FMEA logic

Payganeh¹,

Sadat²

2015

JMT

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Section: -Describing the Methodsmentioning

confidence: 99%

Dimensional calibration (CMM) scheduling of manufactured fixture’s locators, using the M-FMEA logic

Payganeh¹,

Sadat²

2015

JMT

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“…In this paper, the transfer function mechanism 39 is used to model in-plane and out-of-plane variations in the assembly process. At each assembly operation, transfer function is utilized to aggregate new variation generated by the corresponding variation source (in order to directly mapping the input deviations to output variations).…”

Section: Multi-station Sheet Metal Assembly Processmentioning

confidence: 99%

Integration of in-plane and out-of-plane dimensional variation in multi-station assembly process for automotive body assembly

Shahi

Masoumi

2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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Automotive body assembly systems contain multiple operations in multi-station processes. One of the most critical challenges for such manufacturing systems is dimensional quality, which is affected by the accumulation and propagation of variation caused by manufacturing imperfections. However, sheet metal part compliancy behavior makes the variation modeling method extremely intricate when both rigid (in-plane) and compliant (out-of-plane) variations are considered. This paper develops a more accurate variation propagation model to describe dimensional variation of sheet metal assembly in multi-station assembly system through involving both the variation types simultaneously as well as the impacts of assembly operations on each other. In this methodology, three sources of deviations—non-ideal parts, fixture errors, and assembly operations effects—are taken into account. The variation generated in every assembly operation (placing, clamping, fastening, and releasing steps) and the variation propagation through station-to-station interaction (repositioning) are analyzed by the transfer function mechanism. In the in-plane direction, the stream of variation analysis is adopted to obtain the rigid transfer function to describe the position and orientation relationships between part and assembly element errors. For the simulation of part deformation during the assembly process in the out-of-plane direction, the compliant transfer functions are extracted by variation response methodology. A nested state space model is used to integrate the overall assembly variation by updating part geometry after each assembly operation. The capability of proposed method is illustrated through a case study on an automotive body side assembly process.

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“…This propagation of manufacturing disturbances affect the behavior of the production network [23], and their impact on the shop floor, the most sensitive part of a manufacturing system and where customer value is created [38], depends on the associated consequences derived from their propagation [31,32,39]. For this reason, authors like [44][45][46][47] have proposed models that try to predict the effects of manufacturing disturbance propagation (in this case, dimensional variation propagation), representing the disturbance propagation in terms of state-time equations (of some sort). If we take into account that (i) robustness and resilience are necessary to respond to disruptions [24], (ii) the topology of the manufacturing system affects its robustness and resilience [48], and (iii) in order to increase its robustness, a manufacturing system must be modelled and the disturbances' negative effects studied [21], it becomes evident the need of a tool that facilitates the modelling of the propagation of a disturbance, from the manufacturing system structure point of view.…”

Section: Robustness Resilience and Production Disturbances Propagatmentioning

confidence: 99%

A Max-Plus Algebra Approach to Study Time Disturbance Propagation within a Robustness Improvement Context

Martínez-Olvera

Mora-Vargas

2018

Mathematical Problems in Engineering

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Industry 4.0 aims to ensure the future competitiveness of the manufacturing industry, where one of the major challenges faced by its implementation is the manufacturing/production system robustness (that is, able to perform in the presence of noise), as they may not be able to absorb input disruptions without bending or breaking. In this paper we propose to use the Max-Plus algebra approach to study the propagation of manufacturing disturbances (i.e., processing time variations), presenting a case study and performing a sensitivity analysis, with the idea of understanding under which conditions disturbance propagation takes place. Findings show that the impact propagation depends on where the variation source is located within the manufacturing system. Two are the main original contributions of this paper: the use of Max-Plus algebra to study the impact propagation of processing time variations and a four-step methodology to derive the equations representing the deterministic manufacturing system.

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Transfer Function of Assembly Process with Compliant Non-ideal Parts

Cited by 20 publications

References 22 publications

Dimensional calibration (CMM) scheduling of manufactured fixture’s locators, using the M-FMEA logic

Dimensional calibration (CMM) scheduling of manufactured fixture’s locators, using the M-FMEA logic

Integration of in-plane and out-of-plane dimensional variation in multi-station assembly process for automotive body assembly

A Max-Plus Algebra Approach to Study Time Disturbance Propagation within a Robustness Improvement Context

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